Constraint programming using block-based workflows

Abstract

Embodiments presented herein provide techniques for executing a block-based (BB) workflow to solve a constraint programming (CP) model related to a semiconductor manufacturing environment. Embodiments include receiving at least one BB workflow comprising a plurality of blocks. The plurality of blocks may specify a set of operations. Embodiments include accessing a plurality of block definitions corresponding to the plurality of blocks. Embodiments include executing the at least one BB workflow by performing the set of operations based on the plurality of block definitions, including extracting data from the semiconductor manufacturing environment, the data comprising both static data and dynamic data related to equipment in the manufacturing environment, creating the CP model based on the data and at least one constraint defined in the BB workflow, using a solver to determine a solution to the CP model; and publishing the solution to at least one component in the semiconductor manufacturing environment.

Description

RELATED APPLICATIONS[0001]This application claims the benefit of U.S. Provisional Application No. 62 / 697,217, entitled “CONSTRAINT PROGRAMMING USING BLOCK-BASED WORKFLOWS,” by the same inventors, filed 12 Jul. 2018, the contents of which are incorporated herein in their entirety.BACKGROUNDField[0002]Embodiments of the present disclosure generally relate to constraint programming, and more particularly to techniques for using block-based workflows for constraint programming.Description of the Related Art[0003]Manufacturing facilities across many different industries are responsible for producing products that are used in every facet of life. In the case of semiconductor manufacturing, for example, semiconductor manufacturing facilities manufacture products such as, microprocessors, memory chips, microcontrollers, and other semiconductor devices that have a ubiquitous presence in everyday life. These semiconductor devices are used in a wide variety of applications, examples of which i...

AI Technical Summary

Benefits of technology

Enables manufacturing facilities to adapt scheduling systems to changing conditions without specialized programming knowledge, reducing costs and improving productivity by allowing users to configure and maintain CP processes easily.

Problems solved by technology

Each manufacturing environment is unique and extremely complex, often requiring immense amounts of capital for the necessary equipment, tools, facilities, etc.

Scheduling in a manufacturing facility involves making complicated decisions about what operations should be performed and the order of these operations.

Typical scheduling problems involve creating search variables for each task, including at least one variable to represent the equipment that can process a task and at least another variable to represent the start time for the task.

Custom code, however, can be difficult to maintain and inflexible, which makes it difficult to make modifications.

With constraint programming models that are created using custom code, however, adapting to such changes can require a level of technical expertise that may not be available to the manufacturing facility (e.g., an end user may not have coding experience, etc.), require a significant time commitment, substantial costs (e.g., due to the complexity of the facility), etc.

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